{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Multilayer Perceptron (MLP) \n",
    "(c) Deniz Yuret, 2019\n",
    "* Objectives: Stack multiple layers, demonstrate the power of nonlinear activation functions, use regularization and dropout to address overfitting.\n",
    "* Prerequisites: [Linear models](30.lin.ipynb), [MNIST](20.mnist.ipynb)\n",
    "* New functions: \n",
    "[relu](http://denizyuret.github.io/Knet.jl/latest/reference/#Knet.relu), \n",
    "[dropout](http://denizyuret.github.io/Knet.jl/latest/reference/#Knet.dropout), \n",
    "[param, param0](http://denizyuret.github.io/Knet.jl/latest/reference/#Knet.param), \n",
    "[xavier](http://denizyuret.github.io/Knet.jl/latest/reference/#Knet.xavier), \n",
    "[training](http://denizyuret.github.io/Knet.jl/latest/reference/#Knet.training), \n",
    "[gc](http://denizyuret.github.io/Knet.jl/latest/reference/#Knet.gc)\n",
    "\n",
    "![image](https://github.com/denizyuret/Knet.jl/blob/master/docs/src/images/neural_net2.jpeg?raw=true)\n",
    "([image source](http://cs231n.github.io/neural-networks-1))\n",
    "\n",
    "A multilayer perceptron, i.e. a fully connected feed-forward neural network, is basically a bunch of linear layers stuck together with non-linearities in between. In this notebook we will first chain together a couple of linear layers and see that it has no effect on performance (multiple linear layers still compute a linear function). However with a one line change (adding an elementwise nonlinear function between layers) the accuracy will go from 92% to 98%! It turns out the class of functions that can be represented by linear models is severely restricted and does not contain good MNIST classifiers. MLPs have no such restrictions, being **universal function approximators** they can represent any classifier given large enough layers and learn the correct classifier with sufficient data. \n",
    "\n",
    "Simple models with low capacity, e.g. the linear model, have an **underfitting** problem: the error does not drop to 0 even on the training set. Models with high capacity, e.g. MLP, have an **overfitting** problem: even when the training set error goes to 0, the test set error remains high. We will implement two methods to fight overfitting: **regularization** and **dropout**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Set display width, load packages, import symbols\n",
    "ENV[\"COLUMNS\"]=72\n",
    "using Pkg; for p in (\"Knet\",\"IterTools\",\"Plots\"); haskey(Pkg.installed(),p) || Pkg.add(p); end\n",
    "using Knet: Knet, dir, zeroone, progress, sgd, load, save, gc, Param, KnetArray, gpu, Data, nll, relu, training, dropout # param, param0, xavier\n",
    "using Statistics: mean\n",
    "using Base.Iterators: flatten\n",
    "using IterTools: ncycle, takenth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Loading MNIST...\n",
      "└ @ Main /kuacc/users/dyuret/.julia/dev/Knet/data/mnist.jl:33\n"
     ]
    }
   ],
   "source": [
    "# Load data (see mnist.ipynb)\n",
    "include(Knet.dir(\"data\",\"mnist.jl\"))  # Load data\n",
    "dtrn,dtst = mnistdata(xsize=(784,:)); # dtrn and dtst = [ (x1,y1), (x2,y2), ... ] where xi,yi are minibatches of 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "trainresults (generic function with 1 method)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For running experiments\n",
    "function trainresults(file,model; o...)\n",
    "    if (print(\"Train from scratch? \"); readline()[1]=='y')\n",
    "        r = ((model(dtrn), model(dtst), zeroone(model,dtrn), zeroone(model,dtst))\n",
    "             for x in takenth(progress(sgd(model,ncycle(dtrn,100))),length(dtrn)))\n",
    "        r = reshape(collect(Float32,flatten(r)),(4,:))\n",
    "        Knet.save(file,\"results\",r)\n",
    "        Knet.gc() # To save gpu memory\n",
    "    else\n",
    "        isfile(file) || download(\"http://people.csail.mit.edu/deniz/models/tutorial/$file\",file)\n",
    "        r = Knet.load(file,\"results\")\n",
    "    end\n",
    "    println(minimum(r,dims=2))\n",
    "    return r\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "atype (generic function with 1 method)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Some utilities to make model definitions easier:\n",
    "param(d...; init=xavier, atype=atype())=Param(atype(init(d...)))\n",
    "param0(d...; atype=atype())=param(d...; init=zeros, atype=atype)\n",
    "xavier(o,i) = (s = sqrt(2/(i+o)); 2s .* rand(o,i) .- s)\n",
    "atype()=(gpu() >= 0 ? KnetArray{Float32} : Array{Float32})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## A generic multilayer model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Let's define a chain of layers\n",
    "struct Chain\n",
    "    layers\n",
    "    Chain(layers...) = new(layers)\n",
    "end\n",
    "(c::Chain)(x) = (for l in c.layers; x = l(x); end; x)\n",
    "(c::Chain)(x,y) = nll(c(x),y)\n",
    "(c::Chain)(d::Data) = mean(c(x,y) for (x,y) in d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Multiple linear layers do not improve over a single linear layer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Define a linear layer (See lin.ipynb):\n",
    "struct Layer0; w; b; end\n",
    "Layer0(i::Int,o::Int) = Layer0(param(o,i),param0(o))\n",
    "(l::Layer0)(x) = (l.w * x .+ l.b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(\"64×784 Param{KnetArray{Float32,2}}\", \"64-element Param{KnetArray{Float32,1}}\")\n",
      "(\"10×64 Param{KnetArray{Float32,2}}\", \"10-element Param{KnetArray{Float32,1}}\")\n"
     ]
    }
   ],
   "source": [
    "# Here is an example two layer model\n",
    "model=Chain(Layer0(784,64), Layer0(64,10))\n",
    "println.(summary.((l.w,l.b)) for l in model.layers);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train from scratch? stdin> y\n",
      "2.05e-01  100.00%┣████████████████▉┫ 60000/60000 [01:12/01:12, 830.84i/s]\n",
      "Float32[0.242202; 0.285672; 0.0698167; 0.0796]\n"
     ]
    }
   ],
   "source": [
    "# Train the two layer model\n",
    "# 2.04e-01  100.00%┣████████████████┫ 60000/60000 [00:51/00:51, 1179.52i/s]\n",
    "# [0.240742; 0.282535; 0.0691333; 0.0794]\n",
    "mlp1 = trainresults(\"mlp113a.jld2\", model);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(\"10×784 Param{KnetArray{Float32,2}}\", \"10-element Param{KnetArray{Float32,1}}\")\n"
     ]
    }
   ],
   "source": [
    "# Here is a single layer (linear) model\n",
    "model=Chain(Layer0(784,10))\n",
    "println.(summary.((l.w,l.b)) for l in model.layers);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train from scratch? stdin> y\n",
      "2.29e-01  100.00%┣████████████████┫ 60000/60000 [00:57/00:57, 1045.75i/s]\n",
      "Float32[0.241826; 0.266971; 0.06695; 0.0749]\n"
     ]
    }
   ],
   "source": [
    "# Train the single layer (linear) model\n",
    "# 2.30e-01  100.00%┣████████████████┫ 60000/60000 [00:40/00:40, 1502.26i/s]\n",
    "# [0.242363; 0.267073; 0.0671333; 0.0746]\n",
    "lin1 = trainresults(\"mlp113b.jld2\", model);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "using Plots; default(fmt=:png,ls=:auto)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# multilinear converges to a similar solution, not identical because problem is non-convex\n",
    "plot([lin1[1,:], lin1[2,:], mlp1[1,:], mlp1[2,:]], ylim=(0.0,0.4),\n",
    "    labels=[:trnLin :tstLin :trnMulti :tstMulti],xlabel=\"Epochs\",ylabel=\"Loss\")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# error results also close to the linear model\n",
    "plot([lin1[3,:], lin1[4,:], mlp1[3,:], mlp1[4,:]], ylim=(0.0,0.1),\n",
    "    labels=[:trnLin,:tstLin,:trnMulti,:tstMulti], xlabel=\"Epochs\", ylabel=\"Error\")  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Multiple linear layers are useless because they are equivalent to a single linear layer\n",
    "If we write down what is being computed and do some algebra, we can show that what is being computed is still an affine function of the input, i.e. stacking multiple linear layers does not increase the representational capacity of the model:\n",
    "\n",
    "\\begin{align*}\n",
    "\\hat{p} &= \\mbox{soft}(W_2 (W_1 x + b_1) + b_2) \\\\\n",
    "&= \\mbox{soft}((W_2 W_1)\\, x + W_2 b_1 + b_2) \\\\\n",
    "&= \\mbox{soft}(W x + b)\n",
    "\\end{align*}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Multi Layer Perceptron (MLP) adds non-linearities between layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Using nonlinearities between layers results in a model with higher capacity and helps underfitting\n",
    "# relu(x)=max(0,x) is a popular function used for this purpose, it replaces all negative values with zeros.\n",
    "struct Layer1; w; b; f; end\n",
    "Layer1(i::Int,o::Int,f=relu) = Layer1(param(o,i),param0(o),f)\n",
    "(l::Layer1)(x) = l.f.(l.w * x .+ l.b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train from scratch? stdin> y\n",
      "7.00e-03  100.00%┣████████████████▉┫ 60000/60000 [03:05/03:05, 323.79i/s]\n",
      "Float32[0.0053576; 0.079804; 0.000316667; 0.0234]\n"
     ]
    }
   ],
   "source": [
    "# We add a nonlinear activation function to all but the last layer\n",
    "# 2.83e-02  100.00%┣████████████████┫ 60000/60000 [00:52/00:52, 1150.34i/s]\n",
    "# [0.00636037; 0.084129; 0.000516667; 0.0243]\n",
    "model = Chain(Layer1(784,64), Layer1(64,10,identity))\n",
    "mlp2 = trainresults(\"mlp113c.jld2\", model);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## MLP solves underfitting but still has an overfitting problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MLP solves the underfitting problem!  A more serious overfitting problem remains.\n",
    "plot([lin1[1,:], lin1[2,:], mlp2[1,:], mlp2[2,:]], ylim=(0.0,0.4),\n",
    "     labels=[:trnLin :tstLin :trnMLP :tstMLP],xlabel=\"Epochs\",ylabel=\"Loss\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test error improves from 7.5% to 2.5%!\n",
    "plot([lin1[3,:], lin1[4,:], mlp2[3,:], mlp2[4,:]], ylim=(0.0,0.1),\n",
    "    labels=[:trnLin,:tstLin,:trnMLP,:tstMLP], xlabel=\"Epochs\", ylabel=\"Error\")  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## MLP with L1/L2 regularization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# We add two new fields for L1 and L2 regularization\n",
    "struct Chain2\n",
    "    layers; λ1; λ2\n",
    "    Chain2(layers...; λ1=0, λ2=0) = new(layers, λ1, λ2)\n",
    "end\n",
    "\n",
    "# The prediction and average loss do not change\n",
    "(c::Chain2)(x) = (for l in c.layers; x = l(x); end; x)\n",
    "(c::Chain2)(d::Data) = mean(c(x,y) for (x,y) in d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# The loss function penalizes the L1 and/or L2 norms of parameters during training\n",
    "function (c::Chain2)(x,y)\n",
    "    loss = nll(c(x),y)\n",
    "    if training() # Only apply regularization during training, only to weights, not biases.\n",
    "        c.λ1 != 0 && (loss += c.λ1 * sum(sum(abs, l.w) for l in c.layers))\n",
    "        c.λ2 != 0 && (loss += c.λ2 * sum(sum(abs2,l.w) for l in c.layers))\n",
    "    end\n",
    "    return loss\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train from scratch? stdin> y\n",
      "1.96e-01  100.00%┣████████████████▉┫ 60000/60000 [01:13/01:13, 820.10i/s]\n",
      "Float32[0.0273971; 0.0801754; 0.00728333; 0.0237]\n"
     ]
    }
   ],
   "source": [
    "# 1.94e-01  100.00%┣████████████████┫ 60000/60000 [00:57/00:57, 1058.05i/s]\n",
    "# [0.026522; 0.0802438; 0.00688333; 0.0231]\n",
    "model = Chain2(Layer1(784,64), Layer1(64,10,identity); λ1=4f-5)\n",
    "mlp3 = trainresults(\"mlp113d.jld2\", model);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# overfitting less, test loss improves from 0.0841 to 0.0802\n",
    "plot([mlp2[1,:], mlp2[2,:], mlp3[1,:], mlp3[2,:]], ylim=(0.0,0.15),\n",
    "     labels=[:trnMLP :tstMLP :trnL1 :tstL1],xlabel=\"Epochs\",ylabel=\"Loss\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test error also improves: 0.0243 -> 0.0231\n",
    "plot([mlp2[3,:], mlp2[4,:], mlp3[3,:], mlp3[4,:]], ylim=(0.0,0.04),\n",
    "     labels=[:trnMLP :tstMLP :trnL1 :tstL1],xlabel=\"Epochs\",ylabel=\"Error\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## MLP with dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "\\begin{verbatim}\n",
       "dropout(x, p; drop, seed)\n",
       "\\end{verbatim}\n",
       "Given an array \\texttt{x} and probability \\texttt{0<=p<=1} return an array \\texttt{y} in which each element is 0 with probability \\texttt{p} or \\texttt{x[i]/(1-p)} with probability \\texttt{1-p}. Just return \\texttt{x} if \\texttt{p==0}, or \\texttt{drop=false}. By default \\texttt{drop=true} in a \\texttt{@diff} context, \\texttt{drop=false} otherwise.  Specify a non-zero \\texttt{seed::Number} to set the random number seed for reproducible results. See \\href{http://www.jmlr.org/papers/v15/srivastava14a.html}{(Srivastava et al. 2014)} for a reference.\n",
       "\n"
      ],
      "text/markdown": [
       "```\n",
       "dropout(x, p; drop, seed)\n",
       "```\n",
       "\n",
       "Given an array `x` and probability `0<=p<=1` return an array `y` in which each element is 0 with probability `p` or `x[i]/(1-p)` with probability `1-p`. Just return `x` if `p==0`, or `drop=false`. By default `drop=true` in a `@diff` context, `drop=false` otherwise.  Specify a non-zero `seed::Number` to set the random number seed for reproducible results. See [(Srivastava et al. 2014)](http://www.jmlr.org/papers/v15/srivastava14a.html) for a reference.\n"
      ],
      "text/plain": [
       "\u001b[36m  dropout(x, p; drop, seed)\u001b[39m\n",
       "\n",
       "  Given an array \u001b[36mx\u001b[39m and probability \u001b[36m0<=p<=1\u001b[39m return an array \u001b[36my\u001b[39m in which\n",
       "  each element is 0 with probability \u001b[36mp\u001b[39m or \u001b[36mx[i]/(1-p)\u001b[39m with probability\n",
       "  \u001b[36m1-p\u001b[39m. Just return \u001b[36mx\u001b[39m if \u001b[36mp==0\u001b[39m, or \u001b[36mdrop=false\u001b[39m. By default \u001b[36mdrop=true\u001b[39m in a\n",
       "  \u001b[36m@diff\u001b[39m context, \u001b[36mdrop=false\u001b[39m otherwise. Specify a non-zero \u001b[36mseed::Number\u001b[39m\n",
       "  to set the random number seed for reproducible results. See\n",
       "  (Srivastava et al. 2014)\n",
       "  (http://www.jmlr.org/papers/v15/srivastava14a.html) for a reference."
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@doc dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Dropout is another way to address overfitting\n",
    "struct Layer2; w; b; f; pdrop; end\n",
    "Layer2(i::Int,o::Int,f=relu; pdrop=0) = Layer2(param(o,i),param0(o),f,pdrop)\n",
    "(l::Layer2)(x) = l.f.(l.w * dropout(x,l.pdrop) .+ l.b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train from scratch? stdin> y\n",
      "1.42e-01  100.00%┣████████████████▉┫ 60000/60000 [01:15/01:15, 796.05i/s]\n",
      "Float32[0.0129755; 0.0667045; 0.00341667; 0.0195]\n"
     ]
    }
   ],
   "source": [
    "# 1.06e-01  100.00%┣████████████████┫ 60000/60000 [00:53/00:53, 1142.58i/s]\n",
    "# [0.0144843; 0.067272; 0.00376667; 0.0189]\n",
    "model = Chain(Layer2(784,64,pdrop=0.2), Layer2(64,10,identity))\n",
    "mlp4 = trainresults(\"mlp113e.jld2\", model);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
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0ubXyrCk/iOdczrf0YFZW1k8//TR//vysrKy9e/euXLly3rx5X3zxxeWXjBkz5vz58wgh7yXXXHPNxo0bFy5ceNNNN23cuNFisXgPZWdnL1iw4MEHH6yurg76m9ZF4UuE2dnZer0+Ozs7Ojp6+/btCKEdO3bcf//9voRXVVX10ksvrV69Ojs7e9y4cS+99FLYYuuEt469e6GhaLQOE51qQJekQiQZNpkxdt8sDgDozsxuC0LIwThplmZ51uq2IYSstI1HyM3SDo8ziOdcbv369QihLVu2IIRyc3NffvllhJDRaNyyZcvatWvff//9yy/RaDQmk8m7nZubm5qaSpLktm3bPvroI4qivLdCCDmdzuzs7IEDB27atCmY71cwhC8RHjhwYPbs2QKBYPbs2d4FjlNTU5cuXeo7oaqqatq0aZmZmUKh8JprrikrK2v7ZpF32+Cb09UpA9XYhPL6mtJLuolKx8+UX31jpAIDAPRoN2begBAaGzsyQRGnEMinp05DCM1Kny4kBGmq5OExg4N4jn/Lly9PSUlBCM2aNQvDsGHDhtF0K40+9fX1Wq3Wd4nRaLz99tuFQqFQKLztttsOHz7sPTR9+nSCIBYsWHDq1Kmuv0vBFb5eoyaTSa/XI4T0en19fT1CaOjQoc1PGD58+PDhwxFCLMt++OGHU6ZMaetWDodj7ty5AoGgxf4FCxbcfvvt9fX1BEFgGNbqtcFS6zIZHbUDNJllGlHO4drhUnFIX677o2nabrdzHNf+qSCoLBYLRVEOhyPSgVxx6uvrMQzDuzCllN1uD2I8QadSqbwbEom/Jcd///33jIyM5pc0f/yy7CXdCTEM6/RTwuPx1NXV0TRts9l4nm//gj9DIsl2Ml34EiHP8953h+d5P2/E0aNH33333ZEjRzZvO2xBKBT+7W9/i4mJabE/Li5OqVQ6nU6lUhnqRGjBbSIkViqVeBLuKjMrlVf6Ekxut5sgCHgfIoKiKP+PKhAKLpdLqVR2JRGKRKIgxhNEvqUH/XM4HEePHt22bdsLL7zg2zl69OitW7fec889PM9v3bp1zJgx3v07d+5cvnz5F1980emxFiRJKpVKmqZxHA/8UUMQRLvnhC8RarVao9EYHx9fV1cXFRV1+Qk8z7/zzjt5eXlr1qyJj4/3cyuCIEaPHu0ts1+OoiiKokKdCFM1yQmqeAonE/rJpMdqSILE8Ete0f77D5KR0zDiShmpyXGc952PdCBXHOpPkQ7kiuN927uSCAN5Rodf86UH2+JdetA7jvCpp55KT0/3Hbr77rvffvvtJUuWYBg2YsSIu+66y7ufZdkbb7wxISHh8ccf71xgGIZRFMXzfNA/8OF7TI8dO3bXrl233377rl27xo8fjxDKyckZMmSI74STJ08ePHjwzTffJAjC6XQihMTibl3f+Ojep1+Ysm5EIvUHSdgrXbL4S6K1H9pJyNWi/qMiFR4AAHRCi6UHmy8r2NbSg82PKhSKVlPdihUrVqxYEcxAgyd8nWWWLVtWWFi4ePHi4uLiJUuWIIRWr17d/IScnJzy8vK5c+fe8KewxdY5/7j6WSEhSFdiB5Vyo9HT4qh0dJb90M6IBAYAACBw4SsRymSyVr9o+L5cLF++vN3yeLeyv+wQzdJXJ0/KG6TL0xGplx6VDJ9i/u/7rNlEKLWRiQ8AALqHJ554ItIh+AMzy3TeQF2/sXEjUdOw+pbdfzChWDz0KseRHyMRGgAAdCNTp06NdAj+QCLsPKVQnmPMRQiN0mEnqlnW1TIXSsddaz/4PxRwN18AAADhB4mw83AML2woZnl2TDSuy2uwlbecqUGQkCEaOI5z2iISHgAAgEBcKZ37Q2TpwBs5no8Ro52x2if0xOUDW1RzV0UgLAAACIHetwCTF5QIu+S/F3Z9X7AbIXT5Ir0AANATtboMk29nL1uAyQtKhF0yK326d2OUDsstoekoUqCAtxQA0IO1ugxTi53eBZgaGxs/+eSTtWvXhiu0UIGndpewPPuPw5sfGn33aB32288NlXYs+fqWE79xDltD9mvaW59EIZ7sBgDQC9TnWjnmkuolqUEojhYihGizh3Vzvm1Lcct+CdqBcozAEEKWQrs8SeLbpq2XTPgpVJHypNbn5PMtwzR37tz333+fYZhly5Z5s+CqVS0besaMGfP5558jhLKysh5//PG3335769atmzZtOnbsGIZhw4cPv+uuuxQKRVZW1ooVKz777LOEhITHHnvs8tkxIw6qRruEwIh5fa/HMDQiCvuPSFH7hxldVj+KS2SMqcqdnxOJAAEAPYzppKXueGPz/xw1bu8hd6On+XaL0+qON/oyqPmCvfl2i9MsRW1O0e5bhmnz5s0bN2584403Dh482HxtpuZaLMD08ssvb9q0qcetwYSgRNh1Ukpcaa2Okxt4rZBpJMyFdmWatOU5Y6+1H/yfMGNoq3cAAACfPovj2jrUvBgnT5Jk3prY1pkJ10S3uh24wYMHv/fee1lZWRs2bGjrnBYLMKlUqt9///29994TCoUIodtuu23lypXeo741mPysphBBUCLsqhJLeY29FiE0PhqrSFLU/mG+/BzJyGmuc8c4W2PYowMAgM545plnZs+efeDAgb/97W9tnXP5AkwoZGswhRQkwq4abRjuXeJysgHbqVDUnTTzbMvqUVwkFQ+aYD8IU48CAHoAhmGWLl1qMBiWLl2an5/v2+k7weFw7Nu3b9u2bYsXL25+oXcNJpqm3W53izWYWJbtyhpMIQVVo13F8dy9Pzz+1jUvTI3FHjlMPJQscdS4pbEtlxmTTZlbt/lJ2bQFV87CTACAnsi7DNOiRYvuu+8+giC81Zu+tZn8LMCEQrkGU0jBQ7mrcAx/e/qLCKEEKZKQGD4/UapqpXcoZUjW3voEhnfH5ccAAMDHtzpC8yWAWiyZ0IJv7YSeuAYTgqrRoDhSdfy3iiMIoSkG7JfqNofVC1IGwAgKAADobiARBkG8PLavJh0hNDkG+6WKZ2nOVU9HOigAAOgWuvkaTAgSYVDopdFGRy1CaLIB+7mKsxTYrZcNdPVh6irDGBoAAERYN1+DCUEiDJafivdxPJcixwQ4Vhcr0w2/fP5thBDiPbTxtQeZuqowhwcAAKAtkAiDAMewe0eswDEcITQpxl8zIUYJpONm2PZ9FcboAAAA+AOJMDi+yd/57YUfEEKTDdgvVTxHc8ajrQ+fl02c5Tj6E+ewhjdAAAAArYNEGBw39Ln2+vRrUFMzIY8RWNE31a12mSGUWlH/0fZDu8IeIwAAgFZAIgwOjufey/mYR3y6AsMQKnIg3XBlzaGGVk+WT5ln2/cVzzKtHgUAABBOMKA+OHAMH6YfxPMIw9BVMdjPVfzNE7U5bxQmXBONky3HDlLx6YKU/mxDLRlliEi0AIBuwmg0HjlyJNJR9AAhXQEYEmHQZGjSqu01sbIYbzPh7RkCWbyo7rg5epTq8pO1t3T3gTUAgFC74YYbPv/887vvvjvSgfQMU6ZMCdGdIREGzbn6Cxa3NVYWM8WAPXucQwjFXqUt+b6m1UQIAADJycn79u2LdBQAEmHwjIgZ4t3IUGIsj4qtfHKmvPGCnfNwONV2WyzHIpiAFAAAIgc6ywTTa0e2nKk7jxCa5J10FEMps2L8ZEG69FztW48ivs1xhwAAAEINEmEwPTBqVf+oDPTnpKPtni9IyEA4bv8dhlIAAEDEQCIMJg/HvHp4E8fz3tGE3p22cmdbg+sRhqnm32P57kPObglflAAAAJqBRBhMFE7OyZiJYShThTkYvtTGI4QoGalIlbR5iSFZPHyK+dutYQwTAADARZAIg0wtUuXWnsMQmhqL767gEUJCFSXSCPxcopixzJV3hC46E64YAQAAXASJMMgsbku9qwEhNCMe+74soF4wuEiimn+Pp6o4pIEBAABoFSTCIEtSJkyMH0uz9IwEfE8lR3NN+3PfKbGWtrlIoXjQOOn4mWEKEQAAQDOQCINv2+ntp2rzdCLUV4Ud+HNJJu1AefG31ZENDAAAwOUgEQbfLYNu8g6uvy4B/66sqUioH6Nm7KzpdDu9Q1mzibW2PlU3AACAUIBEGBLr9r/g8DivS8C+K20qEWI4ljInpujrap7113Bo//2Hhk9ehSH2AAAQNpAIQ2L16HsklHhYFGZj0AVLU1ZT9ZGJdYKq3+r9XKj4y0LObrX99l1YwgQAAACJMDRYnttbcgBD6NpL+46mzIqpP+N3bXqc0Cx9xPK/bYyxPORRAgAAgEQYIjiGiSkRQmhmAvb9n82ECCGJQTRwVbL/a0ldnHLmLaYPN/CMJ6RBAgAAQJAIQ0QpVAyNHmR2W66Jww/W8LYOZjTp+JmkLtay6+PQRAcAAOAiSISh8lPJvjN152UUGqXD9lRyzQ8xDrbqgMn/5epFD8inzAtlgAAAABCC9QhD57q0rKaNRPy7Mv6GpIuHcAoT64T+L8dF0tDFBgAAwAdKhCH0xC/PNrgar0vAvi29ZDwETuGqvrKIhQUAAKAZSIQh9PdJf1OLVBlKTEqhk/WtDQ0MYLig4/Buy3cfBj02AAAAXpAIQ6jB2fh1/v8QQjObjaz3qcuxXPiist2biPqPth/Z7co7GpIQAQCgu+F51myiS885Tx9qvrP2rUdrNt5Z9+ytXNm54L4gtBGGkJgSp6tTEEIzE/D1f7BPDL3ka4eqj/TC5xWJ10QLFP7+CrhMqb3libr31ketWi9IyAhtxAAAEC6cy4EYGpepvD/SpeetP37KGCsYUxUukRNKLaHQiDJHYCSFEEIYppi5HBdJWUpk44NchINEGEJSSmKQ6uscpskx2tMNvMmNtM26yJASQjdMVXXAlDRT7/8+gpT+msUPmN55Wvd/L5G6uNAGDQAAQcKzDEIII5oSjf23713nj7NmE9tg5KyNiKQkQyaqb37Ye5RQqCUjppJRcaQuDhO00p1QmDoQIcTTNGb1Oy1Jx0EiDK3jNae0YvVQiXaqAf++jFuWfskXmbgp2pzXCuOv1hHCdr7giAaMVVxnrtv8ZPTDb+ES6GgDAOh+OM5xbC9TV8nUVTK1lWyjkbNbNcseEw+9ynuc0MZIhlxFqLSESocrNL4E2XRUpROrdJGIGxJhiF2dPMm7MTcZ+7KYX5Z+yVGRRqBMk9Ycboi9StvuraRjppO6OMiCAIBI4WyN7oJTjLHCYyxjaspZi4lz2mOf/6wppeG4O/8EodaJMkeQV91AaPSEXI0wzHe5qO/wiIXuFyTCkFu956l1E1bfkCS/76DHzhDSS9/yuKlRF7ZXBJII0Z81AwAAECo8z9RXe6pKmKpiT2UR01griE9Xzb/be9BTXeY4tpfUxQvTh8gmXE+oojCRtHnBzlfP2bNAIgy5l6c9490Yo8N2lnHzUy6pBZUnigf/X2pH78nTbkQQLSoWAACgHTzPNtYy9TVsfQ1jqmbrazinXTrhOlHmCO/x+k9edefnUIYkypAiGjiG1OhxZZTvamH6IGH6oAiFHkLwJA25KlvNnpL9SwYsmJeC7yjm56e0PKHdBsLLWXd/ypgqNUsfQzgMgAEAtMRaG9jGOraxjm0wso21yutv9z0rat96jFBqCG0MqdEL0gbiYjllSPZdqFn04BX4VIFEGHJKoWJSwjiE0Jwk/PHDHhdLiIiW5/Asby1xKFIDnVZNfs3iuneeash+Xb3ogeZV8ACAKw3voTmHlVA2Na+4zhw2bX0WE4oJVRSp0hEaPaGM4lkGwwUIIYRhMWu3+rvdlZcFESTCMJBQYpMTVdqqY2UxgzTYnkp+ZkLL1OUy0c5aOvBEiFGCqBVP1W1+snHHJl/1PQCgl+FpN2OqYuuryZhkUhvj3Wn75Svn6YOc3cI5rJzdghASD56gWfaY96gwY1js859jlCBiQfdAkAjDocRSHiXWxMpi5ibjO4q5mQkti4TiaKE4up1puFvABCLtyr/Xvf24+b/vK2fdHrxgAQARxfP1n7zK1FaypkrOaSc0MaQ2Rj7tRj/FOGEAACAASURBVF8iFKT2p2KTcYkclypwiaLFkLum4eegIyARhsPE+DEszyKEFqRgz59gN08gyDaqH2gLc/6T8oxFcQJl+59mXCSJWvVs3ZY1jKmK1BqCGzMAIIh4xuNLUaylwV1wkrM0sI21bGMd01jHNhj1j25qGhyFYaLMEcTY6aTWQCg0l7d9wAxTQQeJMEwe3/v3pyY+kiCVJsuw/TX8VEPrDXsCBanqIzvxWuGAvyZJY0Xt3haXKqIffB2aCQHobtgGo6eyiC4v8FRc8JQXkIbkqL82dSBnzXXOk78ScjWh0lEJfUi1jlDpcJHEd61k+JTIBH2lgkQYJi9Ne9q7MTcZ/7KYm2q4rMPMn+KnRQlVZN4HpcMeSidEATRcQxYEIEJ4t5OxWzibmbObyeh43wyIjTs2OU/sp2JTqPh0ybAp1A0rmtfZCBL6aG95IkIhg1ZAIgyTarsxO++r+0euXJCCTfuee30c8pO+dMNVlkJHfnZF5i0Jgb8EazbVb9uoWfaYr/8YACAoeJZh62tIbQzCm77CGl970FN+oZogCakCl6lwmUI6doYvEarm3qmad1fk4gUdA4kwTLRizS2DbkIIZSgxJYV+N/Jjo/2V5FLmGHJeL6g50qAfpQ7wJQilVtRvpPH1B6P+ur75wCAAQEdxDqvz1EGmptRTU84Yy9jGWkKp1d37IvHnZJiapY+YXKwuNg5vdbwB1NP0KJAIw4TCyQZnY5mlcpCu37wU7Mtibmx0m7WjCCGcxPrdlkiK/Z1zOfnVCwl1dO0/H1PNXikZdXXXQgagN/NUFrnOHmNMVbzLybMehBCh1Krm3uk9yjnt7gsnKX2CdMw1ZHQ8qYttMZETGRWLamoiEDcIgXAkQqvVunHjxtzc3IEDBz766KNyubyt/Q0NDZs3bz5+/DiO42PGjFm1apVEIvF/8x7EwzECnEIIzUvG5//IbhzdzvkiTWdGAkmGT6EMyaatz7qLclVz74ThROAKxzmsTF0Va6pmTFVUbKqo/yjvfk9NKWs2UYYUXCTx9ufEhBe7p5HaGM2S1ZGJGIRdOCYRyM7O1uv12dnZ0dHR27dv97P/lVdeiYmJ+fjjjz/66COZTPbRRx+FIbywydCkGeR6F+MepsUQQjn1LdesbxXP8rV/mDv0QpQhWf/wm7hA5F0MDIArU8Onr1Wtu7n677c1bH/DcWI/57A2H3InGTZZNXeVbOL1kpHTxEOvEg+9StRvVASjBREUjkR44MCB2bNnCwSC2bNn79+/38/+nJychQsXUhQlEAgWLVrU/OTeYXve11W2aoTQolTsw/NcIJfwLM95AjqzOUwoVs5Z2bxDNgC9DO+hnacP2fZ/Y/7v+6YPnze+en/lmpvc54/7TpBNvD76oddjN3yuX/2W9rYnlTesEKYPjmDAoNsKR9WoyWTS6/UIIb1eX19f72d/RkbGp59+etNNN3k8nv/85z/NT27ObrdPnjyZoloOOV+yZMm9995bV1eHYRjWLRurbzBcg2hkNBrn6fCsX+T3J9WLifbLhVgKMhqNXXld7sgPWJ+hmCq6Kzfxj6Zph8PBMFAGDTeLxUJRlFgsjnQgocSxfG0FX13MmyqJaYu8+3i3g/n5a1ypRXI1ljQQGzyVUEWZpUrk+8ciUCCaR137t+NHXV0dz/Otd5YBIePxeGw2G8uyAZ6v0WhIsp1MF45EyPO8Ny3xPM9xnJ/9jz766BtvvLF48WKVSjV37lxfa2ILYrH43XffjY+Pb7Ffo9FotVqPx6PVartnIuR47uG9T7045alhWnJ0NPezVb00LdA4aQsjkJP+Rl20zSYU2D9cL508VzplXogWb3K73UKhUKPRhOLmwA+SJCmK6k2t6T5MTZnj0E669DxTVUSqdVRCBhWfLtX4JlvRoruejWR4DKPVaiERhhlN0xRFabWBDhIL5A8UjkSo1WqNRmN8fHxdXV1UVJSf/SKR6Omnn/YW9XJychISWh9Fh+N4enp6SsplCxohhBAiCIIgiO6ZCAlE/OMvfycwAiF0Zz/slVPcLRmB9gst+qJc2UcaNzmq/VMvo/zLQunwyY2f/9P06n3qRQ8Ikvt14ib+EX8K+p2Bfz39neccNk9FAWMsZ60NrNlEKDSKGcuaDuE4qYqSDJ4gSEjHhN2uyOt92yERhlkoPvDh+BOOHTt2165dPM/v2rVr/PjxCKGcnJxW97/zzjuvvfaa3W43mUzvvffenDlzwhBemNU6TJ+d/QYhNCsRL7GhU4F1mUEIpc4zlP9UZ69yde51SY0+auV6xbVLTe+vt+7+tHM3AaCLeLeTc9l9P5q/fqd6/XLL/z6iKwoQQoKEPsKMob6jVEyifNoCYfqgbpgFQW+C8XygD+JOs9lsGzZsKCgo6NOnz+OPPy6VSrOysnbv3n35fovF8vLLL+fk5ERFRc2bN++6665r9YYpKSl79uxpq0RYXV2t1+u7Z4kQIWT3OKrtxjRVMkLoqWNsvRu9OT7QrzbVhxqqfzUNeSANIzr/27GWBk9FgajfyE7foVVut9tut0PVaPiZzebuXDXqLsxlqoo91SWemlLGWMHZzco5K2UTrvce5d1OTCDqocPPa2pqdDodlAjDjKZpq9UaeNVoIMKRCIOuRydChFCNvZZm6QRFXLmdH7qDKVlMSQOuos77oFSiFybN0IcywM6ARBgp3SgRcpynttxTXiDKHIFLFd599f95BSMpSp9I6hPI6HhSHd1D097lIBFGRCgSIcwsEwHF5lIhIUhQxMVLsfF6PLuQuz0j0H9L6fNjj798QTNAIU8MQmURU1vR+Pk/JWOuEQ+ZGKJONKB342mX48hPdEWBp7LIU1VMyFVUfLogKdOXCDU3PxzZCAFoFzz7ImBM7AiO5ziewzF8VT98/R9s4ImQkpOZtyaKo4MzXwyh0UvHzbD99p35yy2S0VnScTPIKFjXELSGY5l6I1NbwdRWsA1G5ey/Nu3HcLosn4pLlYycRsWm4CJpRKMEoDMgEUbGS7+/tbj/vERF/Ix47N7f0B91/PCoQOuLFClBqwTDCNI7pwZTW2E/+D/jaw+I+o7QLHs0WPcHPRHPMrzbiUuaBi+5zhxp3LHJO+s0GRVL6mJJXTzieW8NJ0YJ1IseiGi8AHQVJMLIeGzsfd4NHEMr+uL/Osttntjh3sBF/62OvUorVLW/ln27SF2c8oYVipm3eMoLun430LPwHpouy6dLztLFeZ7KIraxVjJ8inrxQ96jgqS+Uav+Tmj0UHkOeiv4ZEfMU/s3Pjz6boVQfkdfvP/nnhfHEIoOZjTDOE1QsqAPRlKC5Ezfj+7zx6n4PrhEFsSXAN0BzzKI8fjGJJi/focuyxck9RUPnqCYuZyMumSlBVyq8DX4AdArQSKMmEfG3CsTSBFCMWJ0dSz+73zu7v4d634mivqzpZBHnZtxxj/nmSOmrc+JBo6Rjs4Spg/pNZ39rkDOk7+xDTWs2cRaG5maUk91ifK6W2WT53qPqhbcE9nwAIgsSIQRIyJFW09+csugRTiG3TcAv2M/e2c/HO9EruFRzpuFiddEqzODXHRTzVmpyFrkOLqn8at3eKdNMjpLNnEWLlMG91VA0PFup7vglCCxr++PRRef4VmWUGgoQzI5fgYVl4YJRP5vAsCVAxJhxJA4MSR6gHf7qhhMJUC7yvkZCR3PhBhKm2M4835J6hxD1NAgZylcqpBNniObPMdTUWD//QfO5YBE2A3xLnv1KxdLdaytUZCYoZp3l++PpbxhRYRCA6AHgEQYSYOi+x+vOTkiZghC6N7++Ou57IyEzvxFZInigXel5P6rmHGyMeNCMqSdiktTzbvL9yPvoev+tU48cIxkxFRcpgrFKwI/OLvFfmiXdNwMbwsuJpRE3f287ygh1zRfeA8A4B8kwkhiOOasKd+bCBel4Y8fYU/V84M0nWmKk+iFg+5OOb25mHGy8dN03p0eG0PJQvInxghS/peFjmN7LTs/FqYPlo69BkuFld5CiGcZ5/F9bGMt21DL1FfTJWfFgybwHjdCMoQQwjBSCwNAAegkmBwoksSkaMmABRa3FSEkwNGd/Yi38zq8Bq+PSCsY/H+pjedsHlvTooDnPi73HXV0drbu1uG4qO9wzc0PG57eJho4xvLjZ6YNKxAd1Je4UvEe2lNe4Djyo/m/76E/Z0DEMNx19ijntJOGJNnEWTFrPlAvfpBQBnOWKQCuWFAijLBSS8WX57+7f+RKhNBd/fDMzzzPjiS0na3WEijIgXddnIJ14Kpk7wZtZXLfLRGqqNirtNpBiq7M2d0CJhRLx0yXjpnuNFY6yab+F7zbSZeeE6YNRjANY8A8FYWWnds8VSWsuY7UxVExSVRcKs94MEqAEEI4rlkKEx0AEBKQCCMsURHnzYIIIZ0IzU7C3z3LPTYkyPlDICdHPplhOm2t2m86/59ySk4KVdTAVcm4IGgvhCu1yN60vA7bWGf+5n2mvlqUOVI0YLQoc4RvmpIrGs8zpmpPZZGnqshTWczUlhNKbdSqpqVlcblaMuovlCGZ1MYgvKcuLghATxRoIuQ4zuFwyGQyhBBN0xaLpduuAt/jnKo9s7/s0N3Db0cIPTQIv3Yn+9AgnAp2UQrDsajBiqjBCp7j3Y0ed4PHmwV5lucYnhAG8/VIfUL0w2+wjXWuM4edf/zcuP0NKiFDd/eGK2UkIs+zDbWemlLWbKJikwWJfRFCtJVx7tnqyNlPGVIoQ7J46ERKF080m9mVUKjFgydELmgArlwBJcL8/Px169aNHDny4YcfPnPmzBNPPGG325OSktavXx8bGxvqEHu9/lF9B+qalowfqMb6KNCOYu6m1FBVKmI4JtIIRJqmwfiV+0zSWJGqb/CnjyFUUdLxM6XjZ/Ie2lNZ6MuCrNlk/narIKmvILEvFZfamybuatyxiS7K8xjLcLGU0icSah2pifYeqv61Pn7G7RfnqgYAdBsBPYM2b96ckpJy9913I4Teeeed4cOH33fffc8///zmzZvXr18f4gh7PwIj8hsKD1f+sWTAAoTQ/QPxF3NCmAhbiJsaFeqXwCiBIOnizG2YQChMG0SXnrMf/B9TW+ktMymuXdr9q09Zs8m27yvOaeedds7l4Fx21lQVtepZKi7Ne4Ioc4RkxFRSn4iLWk6M3nDepuorC+KE6QCAYAkoEZ4/f/6ee+4Ri8VWq/X06dOvv/66SqWaNm3a5s2bQx3fFSJWFnN9+jXe7VmJ+MOHuMO1/Ghd76xIxMUy6djp0rHTEUI87aLLL9Al5zDqYgch09ZnCYUGE4pxsRQTSXCBWJCcSeriLr8VzzK808YzDKEKTjr3VBbRZfm8y8G5HLzbwdktPOPRLHvMexQjSFwiJ7UGTCTBRVJcLCHU+uYvLeo/utXbcjRnK3NaiuyQCAHohgJKhAKBwOPxIIRycnJEIlFGRgZCCMdxaCMMFiklcTGuVw9vemDUnQSGPTQIX/8H++308NUZmi/YLcWOhL/oAjyf53iPnRXIuxohJhAJUwcKUwc2uzUvHTudqa3k3U7OYePqa3i3E1eofYnQ/O1WZ84BnnZxThtiWUwsFaYN0t62xnuUrTc6Tx/kWQZxrO+W0vEzcXFT3a/9t++ZBiNnt/j+k4z6i3zaAu9RpraCLjiFiSS4SILLVKQ+gYqO990HlynlVy/sxK9pKXYghCxFjk5cCwAItYAeZIMHD96/f//48eO//PLLsWPHkiRpt9t3796dmZnZ/sUgMCJStCBzFo5hCKG/ZuKvnOIOGvlx0WH6qiGJEZ7dVqbOlMni21n4nuf42j/MZbuNmv7ylNkhGMSNYaJ+o1C/No/Lp90oHZ2FCUS4RHb5hJk8xzB1lRhBXtLxkrs4OpNzOTCBUKBK8y6qgEsVxJ/NeAgh8ZCJ4iETg/Wr+AiUVNr8WOORhqDfGQDQdRj/54hdP6qqqp588smysjKVSvXKK68kJiYuW7aMJMmnnnoqOTk59EG2lJKSsmfPnpSUlFaPVldX6/X6Hlpa3XZ6+9XJk2JlMe+c5bYXcbtnhK9QaDzaWPFL3dAH07A2Zv7mOb72mLl0t1GopBKnRyvTpQghj43BCIwUE2632263azQhmeAN+GE2mymKkkig0jXcampqdDodDoNlw4umaavVqtUGczaJgJ6zBoPhvffeq6urUyqVAoEAIfTmm28qlcoemmy6s4nxY2KkeoTQ7X3xV05xe6v4qYYwvcnRI1W1fzTmZ1fET9NJ9C2H9DuN7tx/lQg1VJ+b4pRpUt9+45FGZR9pu+VIAADotgL9LsPzvFgs9mZBmqYZhgllVFeuFFXSiZpTP5f+SmDoyWH42qNs+9cET8bieIGcPL2pyNeaxXNNFQYiraDvsoRBd6c0z4IIobipUZAF/XPUuOvPWL3brLvzU+gBAEIkoESYn5+/ZMmSLVu2IITOnDmzcOHCxYsX//Wvf62srAxxeFeiGFn0cP1ghNDNaXiDG+0qb7/uOlgoOZl8fcyodX0VyU31bLn/KuEYHiGEEZg8yW/CC1+YPQwpwkkxgRBy1LiL/lsd6XAAAC0FlAgvH0f42WefaTQaGD4RCrGyGJvHvrv4ZwJDT4/AnzzKhjnFYDjmW+++/4oknGy/btZcYD//QQXkwlYJlJR31IREL0xfABNQANDtBJQIz58/P2nSJN84wgULFnjHEZ48eTLU8V2ZBDiVKI9HCC1IwVkefVMSsfq0QLIgQkiRImHdXOV3jaU/GIu/rSn8qspa6vQechrdrno6lDECAECXBJQIYRxhmEVJtAaZ/nx9AYbQM8PxNUc5rnsXtjAcS70phpQQiEOkBBdpBKS46aPlrKM91qaWTke1m/NcWY1k9kpX9cF6348cw7sbPRGMBwBwuYASoXccoclkgnGEYVNhq6q2GxFCNyThUgp9VtTd84dQTUVPkydeGx0/TRc7SSvWNfU71fSX+xoXqw/V/7HxQl2OpdOvwnN843lbEMINl/ozVmftxQKxpcB+vtkikQCA7iCgRLhy5cq6urpFixaVlpYuW7YMIXTnnXfW1dWtWrUqxOFdufppMybGj/Wu2btxFLH2WG8oSqXOMfRZFFe223jq7SJ7pxYKLt1prPjF5G7wVOytC3p4oWAusDfvZytPktjKnXy4m30BAP7AOMLua1/Zbzbadn369MkGLFmG3j/Prcrs8UN3lenSoQ+lVR9qOL2pePgj6VRHJmlrzLcZjzYOfSgNp3BVZuvLZbAuLu+D0virdao+0lZPCCee5a0lDsXyBN8eQoSLtAJbhUueCGNOAOguAn2wYhim0+kQQtXV1W63W6VSQRYMtSmJE65Pn+7dfmkM8ffjnKNXjN7EcMwwXqMfo6453IEpxzw25vx/KvosjqdkJCHEpYaWk6t5le+t5Tm+4PNKd0Pkm+Js5S6RVuAdO+GjSJZYi2HSUQC6kUC/j//yyy8ff/xxUVGR98fk5ORly5ZNmjQpZIEBhBDaVbjH5nHM73v9EA02QY+9kcs9HuzF6yMlaUZ0W3O5tYJH5/9Trh+l8l/Oo61M1W/1wx5KF6oo3wgQxsGSksgs+N6iXtRLkSIxnbbETgrmBFEAgK4I6Km6d+/e5557bsKECR988MG333774YcfTpgw4e9///svv/wS6viucFkpU+b3vd67/ewI/JVTbL07shEFTVtZkHGyjflN3WGKvq72WBmEkOmUhXVziddGNz/zwvaKhjxr8z1lPxj1o9RC9cUs6DS6S76vCVbMjedt1lJn4LPDkGJcM0DRYqc8RQLLUADQrQRUIszOzp47d+4tt9zi/TE2NvbWW2+12+3Z2dmTJ08OZXhXOhzDfy79leXYq5Mn9VFi85PxF0+yL4yKTPkmFNyNnvpcq2FC01TdrJvL/VeJIlWi6iNDCMWMU3sbEbWDFaoMWYvcKU+SVP1Wr+7XtJwvz/KOane/WxObnyOOFqYFYww7z/HF/602nbaSYsJhdAvk5PDH+rQ7yDJmXCtTkIs0gqEPpnU9JAB6EHuly2Nnu0PLfasCSoQVFRWLFy9usXPAgAE7d+4MQUjgEoN1/eWCpo4hTw0nBn3hubc/Hi/tJQ20hBD3dRvhaO7MuyXSOFHK9THePeLoi3N/E6KWtRdRw5RF31a7Gz1CFYUQwghs0D2tL0jSdfmfVtBmZuhDaaSYQDxyNdBNWZBHqON/CoGSCnqEAASXx8ZQUtJcaCeEeNfnE2bdnMtEo+6aCAOqGo2Liztz5kyLnXl5efHx8a2eD4JII1afrjt7uvYsQsggQSsy8WeP9/yBFH8ixYQsQYwQ4hj+zPulIo0gfX5sgKmFEOC6YaqaQwH1uDm9ubhzAza84qZGDViZ1NTtBUMijcC7v+ibat8cOi04atweW6/o3QQireLnuvI9ddYSJx+2mTV4lPtuSX2eFSFEyYKwGJwiRRIzVt31+4RIQInwpptu2rFjx0cffVRVVUXTdFVV1UcffbRjx46bbrop1PEBhJCAoAwyvXf7scHEjmLuvLm3DUQ791EZJSXSbwo0C3oZxqmrf2/gOb5yn4l1+ft+ED1Cdf7j8o4O4GNcTXPiSA0ijGglsqTr9G0NhHAa3c2H0jfnbvCc+3dIhtU3PSh7wqeDcYZ1ZZWeqzHfXrnfRJs9Fz6rOLQmr3xPbRhetOZIA45jmn5yZZrUW+MSLF2fWan+tM1lDHKf8IAS4dSpU9esWbN///7ly5dfd911y5cv37dv35NPPjllypTgRgNaNSAqU0BQH53ORgiphWj1YOKxw72nUIgQYhwsIcIzbo7vQD9ShBBCEoNIpKEa8mxinQCn/F0bPUol0gpK/mfs0P0vZFcwDn/Paz/NhNpBCu9c25cTKMmMxXG+HxkXyzhYS7GjYm+d7zHnsTFt5VE/ct8pMV+wn/t3mcvUred3pa1M3tbSrpdvOIa3ljT1PLKVOxl7+8m1Lsfi+34TBuYCO0dzCCHEI1t565UH/hV/W51+Y1zqXMOw1emj1vbVDVMFOcTLsC6u5Pua1LmGi99KedSVGT1Mpy2uOtp7n7ytpTW/t6zFKdhRFeCnvfq3+tL/duxfcSACLfNOnjx58uTJbre7oaFBrVYLhS0XbgUhJSbFI2KGeLcfGIi/e475oYK/Jq6XtBSSEiLj5k5Ws2cuT6DkZCAZNP3G2OMvX9AMkLeVn1q5+S2J7Z+EkNPorjnckHx9DEKoMd/ubqT1o/zVAvmiLdhRVXXARIoIhCGRVqBIkaj6NrUHW0udOIGJdYIAQ0UI1Z0we2yMIlWiTJN2ouWSY3gMQ60WfINOICMxAiv7obZFT+AOYV3cmfdLRGqBPEmCELIUOoTDmsouHitDSgnf+8wxPM/yhBBHCHlsTDjHQDtraZFGIBTgbrMn952SfrcmtvrxMx5rVPeVtVoJOejuFG/kCCFSTHjr52krY69wqduYVqKLynYb1f3k3jYLr/K9de5GOm1eJ/udFX1T3fRPCUN9l8SffKtIGitqfv+k6dGBjHFyGt0V+0z97kygyc43c7SqY4PShEJhTEyMNwv++OOPWVlZwY0GtIXEiQFRmdvzvipqLBHg6IVR+IMHWaZXFQs7SaCkAixHUjIy/ca4c9vK2h29wDjYDtUuClVUfa615veG0l3G8x+XCQPuC5M2zzDx1YFjn+839rl+Qx9KS51r0PRv6gSr6S/3JcVAanRZN1f0TXX6/Njmq2i1y1VP+xoyS76vsVc0PV/slS7vOpShgqGMm+OrD9WbC+ydu4HHxpzaVCTRC/ssaipbx07S+iYqOrut7ODf8o6/cuHctrILn1UeeeZsfW7TSBvDBI03r/Asf/ylCyU7jf4L/Z1AWxjfTOsxY9VCNYUQEqqovjfHn/2wtNWpHmgLk/N6odPYyugoXxZsjnWyWGg6jztr6ZrDDckz9c13xoxTm3Isvo9Hh9jKnRiGZHFNM2CIo4XpN8bmfVBal2Mp/KrKu5OUEghDiEfGo41+/umJo4XDH0n3vp/B1UtGZ18hRsUOT1ImIITmJeNxUvTeeciEHaMZIE9fGCdQND0uqw608iBmnOypfxaZcjswMzguwDNvSSz4sspSaB/6cLoqI5jf010m+tgL+e1ONV66y6jqK5P/uaIyz/LtVsS5Gzyn/lnkq5JKuSFG9md7Z8XeuiPrzxV9XdVUo9VxtrLWX91VTxd9U40QEsjJPoviz39cHkh9Js/yLH3x0+5u8Jx8q0jdT57WRteqQXenjP17Zp+b4tT95eJowdCH0nXDlS3OwQis7/IEj5U59kJ++U+1HB2cf03uBs+pfxa2mlxVfWXx03Rn3ithL3ut+KlRCVm6k/8s8n0gWRdXud/U1quIo4XeIUatamuoq6uerj9jbfWQD+NgUm4wtJj7kBQTiTP0BTsqO9H8XJdjiRpyyZuvHaTQDVcV/7da3feSX4HneOORhsKvq1rcgWN4R03TV4QQ1VhAIuxJUpSJJZby90/+ByH00hji6WNsY7duCeqO1JkykbapvjFqiMLXL7zhrI22MN4hHOpMmXZgy4Hw/klihIP/L3XAqmRBR2ZPDYRIK0ibZ7jwWWXe1tK2Wv5cNbTxWGPyn8NOEEK0hcndUuxn7L/HxpzeUhw3OarVmrqMJfFDHkjFKTznjcIL2ysC6eDAs7y15GLyq26jN69IIzBMbBpeqc6U6YYpz39a3u7j1WF0l/7ZvuusdZ98s9AwXpPkt1oVF+CyeHH0CFXc5Ki2yhASvTD9xtjB/5dqq3Ad3ZDvK8Y5atx1J8ze7ZojDWfeKzEea/TfG8vLZaJP/bPIMEEbf7Wu1RNiJ2llCeL8/zT9yoVfVvneW/1odd+lCWc/KjMebUQI4RTm+6D60bx82bTwJ4/ObStrtUmPFBHe16XNnrYaaOVJkuhRrTRDxoxRcyxf+HWVo7pjk3rUnTC3SIQIoaQZ0cMeTfcNAvbCCCzz1sTGxvif7QAAIABJREFU87bKfZd8A+AYrkPTMXYC8fTTT3fuysLCwl9//XX58uVBjScgr7/++i233KJWt94MY7PZZDJZb50KVUqJU1VJYkocI8byLeh3I39NfLf4NsOyrMfjEYt70lzShBD39Xap+b0hP7vCeLRRFidOm9exzqteAgUZok+dWCeMGa+hGz35n1YwTk6eJGneScftdtuLaG3fS/rmkGLCVu5inaw8sZU8x7jY3M0lUYMVbT2vvXdQ9ZHFjFXbKlwFn1fqR6paraNDCNkqXOV7avOzK6zFjugRKu93ds2ApmccbWFaXNh88lVlurT2D7MiRdJiRtYWBHLS1x6G4ZgyTRo1tOWztdMoKRE1RKlMl9qr3MpUqfclOJb39pYURwlxAqs7YS76qtpa6mTsLCHEvY15drtdKpX6/uhOo/v0puKEv+gME/3Nn6fpJ6/6rUGkFYg0AolBJFRenAhJpBVo+ssvbK8UaQUSvdC3lllbOIY/8coFWbyYkpIFn1VWHaiPGatBGNINV7VacsIp3Ds2t+CLKnOBQ3NpHrKVOf2NcMWQKl1mLXXWHG642ATe3jhaW7nTdMqadGlFK0IIwzC8jQg1/RX52RXOWrpst1E/So3hGE7izcuOLMvSNC2RBNrSHwiM5zvZEvDjjz9u3Lhx9+7dQYwmQCkpKXv27ElJaX30dHV1tV6v762JECHEI/7ZX19dPeYeq0c08AvPgVlkhjLyv6zb7bbb7RpNK3Op9BSsi6vPtUQNU3a082rY0Bam+NtqWYI49iotQshcYCfFBCN1UxR1+XPBUuzI/6R8xOMZLR5VnIc7vaVEFidKnWsI8HVZF9c0oQGPKvebmiZK5VHFz3U1Rxo5Dxc9UhU9UtVKCYZHJ169EDVMGT9NxzhZ2sxIYjrQz87d4CnfW9vpPhrBxTjZhjNWc4EdF+CpcwwIoYqCKrFbqumvQAjZK105bxSmL4iNHtl+r06e5f1U8XlsDCkmAqwDbMizXvi8EiMwVR9ZyuwYQnDJdw7Ow+EUjhAyF9gVKRLfB5t1cTlvFBjGa32lc8Sjom+qk2ZGe88PBG1lSr6t6dOs//PlGvNtzlraML5jjwVbudN4tDF6lNrXsnjJ69K01WrVaoM5W2+Qq3FAGGAIu2v4bWJSJCbRo0OI1b9z31zTeyZdiyBChOtGhLxvelcIFGTz7rU4gfkZv6FIlhBioj7P6uuA42UtdUqiBd5HeYB80/rwHO9rYeUYzlnrTl9gUKS03UkVQ/3/mnx6UxHr4hgXi3iUNr/NrGavdEljLz74OIbP21qqGxG0kl8XkWJCN0LV/BOC4YilmwoSEr1w7PpMXBBQFvGf5Do0gF3dT64fpZbGibSDWlbmW4ocBTsqB9+bait3nttWNuSBNN+IQEKE91+RdPKNQnG0oKlJG0Mps2NQRwhkZPIN7Vyi6iNT9enQXRFCSBYv7vpcNh3i7x0vLS31c9RkarMhF4RalFjz1fnv4+SG+wYM25LXq4ZSgMB5u8bQ5jb78sVN0lbuM3kToctEC9WUt17x8jUxAoQRmK9OEqfw9IX+SgNeAgU56N7U3C3F7kbPiL+1+VDkPFz1oYa0eRfTc8HnleJoQdzkqM6FGgaEBNcmNX3JwAgsPCNPLtfWEBRFikSeJMnbWuqodmXcHN9iXLxII8i8JTHvg1JlqiRzeWIn2gIQhihp01fwmiMNuqHKwEuT3Y2/RHjHHXeELQ7QURMTxmpEahxDr48j7vmVzZlHSqB4Dy4VNURpOmXhGB4nMeORxuiRKlFUBwYmBgslJQbenWwrc/lpCMQp3JcFGSdbe9xsK3MOvj81XDH2TmnzDGfeLYmdFNVqT2ZFiiR1toHyDl3oAp7lG8/ZK3829Vkc17wkZ75gl+iFHVp8O1I630YYQVd4G6FPQWPxgbJDtwxadPNeNl6KXhwdyQrSXtBG2EOZzeZW2wh7roIdVbXHGoc+mBaRtB24mpoanU6H4926GMTRHE7hXUx1gag53FC6yyiQk/qxGt0wJSHETacsUoMo6H9EaCMEl4iTxczJmIkQemMcMXiHZ2EqPjKq96d/0OulzomJnajp5lmwpwiw2bLr9KPV+lHqhrPW6t8bqn+rH/pQ2uXNlt1Wt/4uA/wTkSIJJdlw8DW1kH1xNHHHPrYL0wEC0F1gONZ8BS7QY2BI3U/e79bEIT2tThsSYc9G4eQtgxYRGLE0HU+SYS+fgkwIAIiwSPUb6jRIhD1erCzmm/ydv5Yffms8/uopNq+x5zX6AgBABEEbYW8wOXG8XCBHCK0bRtyxjz0wi+yuI8IBAKDbgRJhb6AUKlyM6/Gf19/dH8MwtOUsVJACAECgIBH2EhJK/NykJxDiNo9nnzrGFluhghQAAAICibD3oAhqe97XdvepR4cQt+8LYAk7AAAAkAh7mcX9542NHXmdodDDo815UEEKAADtg0TY27A8+2PJ3i0T0LpjbIEFioUAANAOSIS9DYER/zfir3ESx/W6rX/dDxWkAADQDkiEvZNcIHt67HUMz/8jBxYJAQAAfyAR9k44hicp4/424MI7p368ABWkAADQtjAlQqvVumbNmrlz565du9ZqtfrZz7LsG2+8MX/+/Pvvv7+uri484fVWM1L63Tn0xmU/nfyp5GCkYwEAgG4qTIkwOztbr9dnZ2dHR0dv377dz/4vvvjCbrd//PHHAwYM+PDDD8MTXi9230A8XqZ7vyDd4rbaPY5IhwMAAN1OmBLhgQMHZs+eLRAIZs+evX//fj/79+zZs3DhQpFItHTp0lmzZoUnvF4MQ+iDqbEnG9TrD+8/X18Q6XAAAKDbCdNcoyaTSa/XI4T0en19fb2f/Uajce/evatXrzYYDI888kird7PZbEOGDLl8PcwVK1Y88sgjtbW1CKErYWHewG0djl934OqrtLY/SrYN0GSmyBOD/hI0TTscDo/HE/Q7A/8sFgtFUWKxuP1TQVDV1tZyHNfNF+btfTwej81mYxgmwPO1Wi1JtpPpwpQIeZ73Ziae5zmO87PfbrfzPP/uu+9+8803r7766ptvvnn53aRS6a5du5KSklrsF4lEYrGYZVmdTgeJsDkdQh9R6I79yq+nTR2k1efWnVUIZCmqlm9gV8AK9ZEiEAh62Qr1PQXHcd1/hfreh6ZpoVAY+Ar1gfyBwpQItVqt0WiMj4+vq6uLiorys1+lUs2bN0/7/+3deXxTVfo/8Ofce5M0W5M03UtX2lLWsssiUIEKiIqAMvIFdEaYcR2cERTnBzIODjIq+h0cxXH7uqEIKuICUpCyFARZBMpaCqULXShpmjRJs9zl/P4I00G6UEqatM3z/oNXc3J78yS99NNz7znnGo1TpkzZsGFDk3sjhBgMhuY+CIZhGIbBILzGhG7whwz448/RO+/keInXK/VmVy0AhKtaezy1jPkPn+wNtR5+8oGCn3xAtMfH7qcf4bBhw3JyciilOTk5I0aMAIBjx4412T548OCtW7d6PJ5Nmzalp6f7p7wg8dwAJkJJFuwXh8YONCoN+ZdPldurAl0UQggFmJ+CcM6cOUVFRTNnziwuLp41axYALFy4sMn2uXPnHjlyZMaMGUeOHHnqqaf8U16QIABrstjcCvrBWQkAxiaOyozs/faRj3A0KUIomBFKO99s6+Tk5Nzc3OTk5CafraqqioqKwlOjzSmw0tHfC5sncIPCCQCcqSnsYUwlcLMfF14jDBSr1YrXCAPi0qVLeI3Q/zwej81ma/01wtbAH2HQ6aEj79zK3rtdNLkAADKMaVuLdljc1kDXhRBCgYFBGIymJDL3p5D7cwXvmtyhilAZIwt0UQghFBgYhEFq+WBWzsKSQyIADI8bfNFWYarH5bkRQsEIgzBIMQQ+yeLWFdEvL0gAUFp30SPhXHiEUDDy0zxC1AEZFfB1NjvhByEihGQnZdW5bab6Gl9NK0QIoc4Ce4RBLTOMrBvLzcgVfjHRvRd/xmmFCKEghEEY7MbEkHdvZe/cKqSEj+sb0avObbv+9yCEUBeCp0YR3J3IWHmYnCO+3H+fkvNMShkX6IoQQsh/MAgRAMCcVOaiA54/MXzXZO6s+XxaWMrNT7FHCKFOAU+Noiv+ksmMiyX3bON/KNrpEtyNN6h1WT46/rn/C0MIoXaFQYj+67VhbLKW2W7+rc3tPFx1rKHdI3qOXjqulWvTwroDQI2zNnA1IoSQj2EQov8iAO+OYnmJLvz5Msuw3kaJSgTI0eoTHMOOiBtyud704fG1ga0TIYR8CIMQ/YqMga/Gc+fsKRvKen526iuT07xoxzKO5X7bd6Z3gwhV+IKhj11yVK/+5f8CWypCCPkEBiG6loqDb2/nvrhAT1lTjUrD8jH/r/HAmXCVcXqPu3hJWHPyy4AUiRBCvoJBiJoQHgKbJ7AfFff+oojKWXnjDVjCRqkjBEnoHd4DAD7IXytS0e9lIoSQD2AQoqYla8mmCeyT+8QNxVJz2yi5kAFRfQGgd3gPlrCHLx+j0Plub4kQCnIYhKhZ/cLIlkncY3vFz883m4VeQ2MHSlQqtZULEvYLEUKdDAYhaklmGMmZxD31s/h18/1CL4YwU1PuKLGWXXJU+6c2hBDyCQxCdB2ZYeSHidzjP10/CwGg2FrKS4IfqkIIIV/BIETXlxlGNk3gHtsrbiy5ThaOTxpjCNEfvXTcP4UhhNDNwyBErTLASDZP5B7bK35y7jpZWOM0W9x1/qkKIYRuHgYhaq0BRpJ7B7fkkPTa8ZayMCG025iEEXsvHsARpAihTgGDEN2ADD3Ju5N9+4z07MGWRodSSsttFYIk4vVChFDHh0GIbkyChuTdyW29SJ/4SZSa6fIxhJnR8x6b2/bC3pUAcKamEKfbI4Q6LAxCdMMilbBjMnfMTB/aLYrNn/4MUxqev/UZAMi5sIMAU2wtww4iQqgDwiBEbaGTQ85ErrKezt4p8s1fMWQIAwBPDv4DQ0huyW4rDqJBCHU8GISojVQcfDeBcwkw7UfB1YoTnw/1mxUq13x0fB0OokEIdSgYhKjt5AysH8eGsGTqNsHZirOeLMP2icggQDALEUIdBwYhuikyBj4fy0Ypyd25xC5ce7ema7CEHRSdebT6xIf5n/unPIQQui4MQnSzWALvj2ZTNHDfXqXJdf3t+0X0+p/e0+s8NolivxAhFHgYhMgHWAL/HkGzIoVh3wpnLNeJN4YwClb+Yf7n5bYK/5SHEEItwCBEvkEAFvX0LOnPZG0SdlZev6s3f/Dvu4XGVtov+aE2hBBqAQYh8qXfpjOf3cbdnytcd0lSADhrPr+jdI8fqkIIoRZwgS4AdTVjY0nuZO7OHLGoDpYOZFoYP9MjLLVHWGphbVF3fZJ3xiFCCPkf/vZBvtdLT/bdzW0tl36zXay/3rSKnaV77bzDL3UhhFATMAhRu4hSQu4dnEYGI74VSuwtXTL8feYcSukp01m/1YYQQlfDIETtRcHC/41mH+vFDPtG2NXi8JnSuosXbeU2j/21A28BwK7Sn5xC0/MwLG7rKz+/8dHxzw9XHWuXohFCwQevEaL29YcMJkFDZuQK/xjC/i696T+8+kb06hvRS5DEmb2mAYDNY2cJk199MloTFakKb9jMVF8TrjI+0Oc3+hCdgpX76Q0ghLo67BGidjexG9k1mXslX5qXJ7awEhvHsDGaKAC4M/V2OSuvtF9SsHKru857CycKdPWRD1yCK0odoWDlO0r2bC/e7be3gBDqwjAIkT9k6MmBKVy9AIM3CqevN+Pea0LKWJ0i9KuC78/XFm8+/6PFZV06cmEIF+J9tn9U39EJI9qzZIRQsMAgRH6ikcFnt7GLMpmsTcL6ouvPMvR6qN//pId1jw+NE+mvvsUQojtfeyGnKLcdKkUIBRe8Roj86oE0ppeBzNgu7q+mLw9ludb9JdY3omfjxjClwag0+Lg+hFDwwR4h8rfB4eTwPVxhHR3/g3DJ2fb9eMfR7Cr9yWeVIYSCEgYhCgCDAr69nZvUjRmyUdhXfVP3oNAptFc/PFDxi93jcIue5iZgBMrRS8cDXQJCqGkYhCgwCMCiTObtW9lp24RVJ1p7yfAaEarwnuE9fqnKp0D/sW8VANQLTjvvOHH59HeFWwBgR0lHWcv067ObK+xVga4CIdQEDEIUSJPiSd5d3PtnpYd2i3a+LXuo5537yg8SIDN63gMAWQkjo9WRg6IzZ/S8xy16al1WADA5zb4tuw0mpNwWwioCXQVCqAkYhCjAUkPJvrs5lkDmBmFP1Q2fJjWE6B4fNBcAUvSJ1zylYOXTeky2uK3vH1vjm1rbyuys7WlM906IRAh1NBiEKPDUHLw7il09kp25Q3xyn+j2aV7oFbpFw+ZXOarP1BT6cr83otRW/m1hztpTXweqAIRQC3D6BOooJnQjR6Zyj+wVh3wjfDyG7W9s4Q5ON6zcVqmVa3y4wxvSP7JP/8g+gXp1hFDLsEeIOpDwEPhyHPtMP2bCFmHxoZbWY7tRg6Iz08O6v3v041qXxWc7bZ06t21B7lIA+Prspm3FO/386gih68IgRB3O7FQmf5qszA59Nwjbym9qcsU1xiaNNoTo/33kQwdff7rm7E/lBwHA4rb68CUaC1VoV479GwDcmTohOymrXV8LIdQGGISoI4pSwsdZ7OvD2d/niTO2iyYfzQnsrk8CgPFJo0M4hVEZFq2OtHscrx98BwB4yXfdz19be2rDJcdlAOAY9rNTX+GQGYQ6GgxC1HHdEU9OTOe6qaHfBn7t+TbONWws1ZDCEjZSFZ6iT9TI1UtvfVqi0jM7npfold5nrctqcVt5kf/+XA4A7L14wOK2mpxm700QbR77Db3c8LghoXItABAgKfrEhldBCHUQGISoQ9PI4LVh7OYJ3Mrj0uQcobTFm923GUOYlWP/xhCyMPevIhWPXz514vIZjuVYhgMAQRIopaIkuEU3APw17yUA2FX6U0HNuevuucJeJWdlKpnS+3BgVD+zs7Y93gJCqM0I7YR/nyYnJ+fm5iYnJzf5bFVVVVRUFCG+HHOIrsvtdjscjrCwsHbavyDBq8ell/PFZ/qxT/djmPb58ToFVwinIHD9vV+wlOgUoQpOoZapWtjslKmgxlk7Kn6Y92F+9ckL1tIpaZN8Uy4AAFitVplMplK1VAZqD5cuXYqIiGAY7E74lcfjsdlsRqPRh/vEHyHqHDgGFmUye+7ivi2VxmwSDpna5Q84JRfSmhQEgGR9olahfWHvSkFq6ZpfD2NqQwoCQL/I3r5NQYTQzcMgRJ1JTz3Ju5P7bRozdZs4c4d4wRbI8xkyhvtH1lJKm714aXXX/b+dy69pfO3AW605p4oQ8hsMQtTJMATm9mAK7uP6h5Gh3wgP7xGrb+JeTjfv1YNvldWVN/mUThH60m1Lr2n805CHexhT278uhFBrYRCiTknFwaJM5tS9MjkDfTfwq05Igs9Gld6YZ4fNjw+Nk5rqF/77yIeN7zhh5x3rT2/0S2kIoVbBIESdWEQI/GsEu+dObmu51OcrYcvFwJwp3VCwKbckr3H7jIwpRuW1o4eUbEhaWHe/1IUQahV/rDVqs9leeumlkydP9unT55lnntFqtS20Hzhw4O23366pqTEajY8++ujgwYP9UCHq1NJ0ZNME7rtS6fG9Yi8DvD6cTdb6dczwPel3MIRQoFcPtLlgKRGpFKY0XLOxjJUl6xNqnLXGRk8hhALCHz3CdevWRUVFrVu3LjIycv369S20i6L44osvPv744xs2bHjwwQdXrlzph/JQ13BXAnPyXu6WCGbIRuHP+8UqP144ZAgpqDn3r0Pv1fPOy/UmADhrPi9Sqc5ta3L7w1X5Fywl/qsPIdQifwThnj17pkyZIpfLp0yZkpeX10K7KIp/+ctfBgwY4HK5ZDKZWq1ubp+iKAqNSFKALhOhjiGEhSUDmDP3yRQs9PyCf3iPWFnvp5dOC0t5fNBDZbbyHaV7AeCbwh9SDckDo/s1ufG4xFGDY/r7qTKE0PX449RoTU1NVFQUAERFRZnN5hba5XL5Lbfc4nQ6p0yZAgD//Oc/m9yh3W7v0aNH4ynzjzzyyOLFi6urqyVJwgn1fubxeOrr691ud6ALAQB4shvcH868cV7Z+wvFzHjXY91dYXJ//JEUCupRuqGVlZWzE6ZXVla2sOWyI6890+9xn9yzvq6uTiaTKZXKm98VuiGXL18WBAEn1PsZz/N2u93j8bRy+/DwcJlM1vI2/ghCSqk3liilV3fammtXKpXffvvt119/vXr16jfffLPxDjUazYEDB5pbWYYQgivL+F97ryxzo2IA3kuGvznoimPcmN2qR3oyT/Vlw3yQO76xOuZlt+CprjclhMbd5K5UKhWuLBMQDMPgyjL+11lXljEajdXV1QBgMpnCw8NbaK+srHz33XcBQKlUTpo0qbS01A/loS4sTk3eGMEemcbZeEhfzz97ULS09u/I9kWAFNaeP2UqCHQhCCG/BOGwYcNycnIopTk5OSNGjACAY8eONdluNBo3bdp0/PhxSunOnTtTU3HeMfKBeDVZNZw9cA93yQnp6/klhwI8B9+rb0SviSljfyo/8FXBd4GuBaGg5o8gnDNnTlFR0cyZM4uLi2fNmgUACxcubLJdLpf/7W9/W7169bRp03bs2PHnP//ZD+WhIJGiJR+MZn+ewtl4yPiSf2CnWGAN/IrzQ2MGTe6efa62KK9sPwCsOfEFAByo+KW51WoQQj6Hd59AvtHRrhG2rNoJ/zolvn1ayophHu3FZMUE+HC5YClhGS4hNC6vbN+o+OGHKo8m6xNtHnt1/eWhMQNb/l68+0Sg4N0nAqKzXiNEqKOJVMILg9ii38hGx5A/7RPT1wv/OCb5c+rhNZL1id5RM6PihwPA4Jj+RqWBAg0L0Tv4+q8KvgcAu8fRml2V1ZW/duCtdq0WoS4GgxAFL40MnujFHJvGfXobW2Sjvb7kp24Tt5V3lJMkybqEVEOKKImphmQA+OuelyQq5ZXtP1x1rMntRSr+fe9r0Zqohwc86ODrL1hxrBlCrYJBiBAMjSDv3MqW3i+7I548/bPY60vhzVOSjQ90WQAAEKrQZkb2BoBXxy5jCJMWlpKkSzhlKvB2Exs4+HqWsL/vP1vGcGqZ6kxNYbmtpYmMCKEGGIQIXaGRwe8zmKPTuLdvZXdW0qTP+Sf3icfNHaR/eEW0OtKoNCTq4rMSRlrc1l+q8r3tHx7//FzthSh1pPfhoOjMW7vdsvHs5qOXjgeuWIQ6B39MqEeocxkdTUZHsxcdzDtnpMk5YqQSfpvO/E93puPMx1fLVGqZqrC2iAKtcFQRlnl84EONNxseN8SoDLtoq4hSRcjY6yyugVDQwh4hQk3rpibLBrHF93MrhrD7q2n3dfx928UtF6nUYbqIaYaUQdGZVfXVF6xNL+EdpY7gGHbrhR21bqufa0OoE8EgRKglDIHsOLImiy2+XzY+jjx3SExZJ7xwRLro6Ch5ODCi35huI1rY4KF+syJV4a/8/IbZWXt1u0twVdebAKDEWta+JSLUsWEQItQqOjk8nMEcvIfbmM1WOWnmBuGurcLn5yWHEOjKWmduv1lhSsOhyqMe0fNj8a5yW2Wlo3rbhZ0AsObkFwDwVcH3ByuPiFTEUTYo2GAQInRj+hvJmyPYspmyGSnMJ+ekuM/4+7aLX16Q6jt2InpvEXzGfI4hbHxonIKVJ+sSZvW+FwAWj3gKACamjO0b0ausrmJHyR4AOFNTGNiCEfIbHCyDUFuoOJiTysxJZWrd8HWJ9F6BNC9PvD2OuTeZ3BHPaDrqwJTZve8FgB5hTaziq5apACBJF5+ki/f2GjOMaSdNZ9IN3XGgDerasEeI0E0xKOChdGbLRO7cDNmEbuTDQinuM/6ebeKac53mrGljclb+xKB5ALCn7GdCmHO1RVZ33TXbrD21gQKtdVnq+Q6whDlCNwGDECHfCA+BuT2YzRO4kpmy6clkfRFNXMs/tV8s7ABLe7fZwwMe5Bj2WPVJj+ipclSb6mvMztple14BgITQbrzI55XtP1NTaPPYt5fkAcCu0p8AYO/FA/nVJwVJ3HphZ2DrR6g1MAgR8jG9HOakMt/ezv4ylQthYdT3wsQtwnelkke6/vd2TNN73BWhCi+xlhVZSsKUhqeH/REARnYbKmfld6dNHBjdzy16NDIVAJTbKynQZH1ClDqynq9nCQMAr/z8Bi/yJqe5zm0L8DtBqCl49wnkG53r7hP+5BbhiwvS22ekYzV0gJGMiSG3RjPDI4nWR9fdOv7dJy5YS5N1CT8UbY9RRybq4v/34L+XjXr2q4LvspOz1DIVS9hAF9hGePeJgGiPu0/gYBmE2peChdmpzOxUxs7DvmqaVyW9eFT8xUT7G8mdCcxdCaSnvov/0ZasSwCASSnjvA+XjHgKAGI1MRqZZkvRdgp0Usr4/RWHRsQNafLbvTnqt2pREMIgRMhPNDLIjiPZcSwAuETYUUG/K5Um/CApWLgrgdybzAyPCorzGHJWDgDD4wYDwB3dx0tUsvP2SnsVAFCgBK79DLYX756SNvGtIx/OH/x7vULn/4JRl4edeoQCIISFSfFk9Ui2dCb3xTjWoCB/2COmrBMWHxJP1Ha+qxU3gyFMqFw7vcddF6ylqw6+c/VT609vPFdbNC9zdoQq/M9DHtErdN8U/lDruna5OF7kAaDCXlXrsjoF15aiXAA4az7vEty8yLtFj9/eC+qkMAgRCrD+RvLcAObEdG5jNitIMDlHzNwgLPhZ/Oy8dMbSgZY2bW/JuoSHBzxocVv3Vxyq89jqeWdW4q2xmhjvs1q5BgAiVEadIjSnKNfsrC0wn1t3eiMA/Gn7YgA4az5fUlfGMRzHsACwv+KQR/TkXz71xZlvAeBY9cmAvTHU4eFgGeQbOFjGVyTqvZRID5voYRM1uegAI5nQjZnZnSRrmzjFGMyWAAAWsElEQVSqO/5gmRtywVJS67I6+Hqn4Lw9+bYmt/mlKj/FkBjChtg99nDV9QdNOAXX2lNfPdRv1o6SPcPjhljdVjkr18jUh6qOec/Qtk3rB8scv3y6d3gGg7+UfAEHyyDU9TEERkaRkVFXfmnWuuGgiX5TIg37VuyuJTO7MzNSmChlYGtsR8n6xKb/wr3KwOh+3i9CuFbdGUvJhTzUbxYA1LqsCk5eUHleLVNlRvYptpYOjxu8eNfyJSMXKLmQm6q7GRKVGMKcNhUoOcUH+WuXj1ncHq+CbhL2CJFvYI+wvQkSbCuna89L35dJUUoSr4Z4NUnQkEjWOTSSGRTTdbOxndk8dq1c8+8jH05JmxSjiQIAB19/rvZCZmTvVw+sfnzg3Pzqk1ZPXXZS1rM7l63Ieq5hOE9reoT/2P/6A31mxGqiAcAteuSsrPFooJY5BZdEpV+qjvWJ6GkI0bf1XXYd7dEjxGuECHUOHAOT4snHWWzVLNmG8ezCfuyIKCJRuruamb6LS10vLPhZ3FlJxc73l22Aea8+3p02MUYTtfbUhryy/QBw1nweAO7LuFvOyjLC0wZH9weAZ275IwB8cmK91Ir+wzeFP1jc1gVDHvWmIAAoWPnKn9+80ZteXbCUfF2wySm41TKVS3Df4JtDrYI9QuQb2CMMFO81wnMu5bcl9NtS6YKN3h7HTIwnE+KYSOwl3iBeEmRMSxeMRCoeqDgyPG5wgfmcjtdERkQ27hF+cmL9rN73nTIVJITGhSq0v9q/yMtYmURpK68X2jx2jVzd0IlcsvvFRcPme5M7aGGPECHUtH5hZMkA5sAU7tg07rZY8k0JzfiSH7JRWHpY3FZOTa5A19dJtJyCAMASdnjcYIlKW4pyKYWtF3Y4+PrqelORpcQtej49+SUA9AhLFSS+T0TGNSkIADJWdrDyyMcnPr+6cd3pjW7RU+uyNH65rRd27is/2PBw2ai/aOWaNSe+EKnYxneImoJBiFCXEqsi83owX45jq2fJVt7C8hK8eFRMW893WyvcmSMsOSR+X0rtfKCr7OQYwjw5+A8MIXJWzhLW6q4rt1UoWHmyPhEAhsYO9C4a0KSB0f0e7Hu/SEUKdO2pDQCQHtZdkIQ3Dr/v4Ouv3tIluKb3uHNE3NCrXpdQoCmGRJawByp/wTOlvoJBiFDXxDEwJoasGMLumMzVPiDLu5Odl8FwDPzvCTHmM37098KyI9K+asp32qXAO4KshJEhnCLNkDIqfjgANLdK3NVYwgqi8Ocfl1BK47QxEpUGRPVVy1TPjVwgZ2S7y/Y1bPmP/a837iYSIN5oLDQXyVjuoq2Cl/57uy8Prh7QJjh9AqGgkKwlyVpyTyIAQL0AeVX0x3Lpsb3SGQvtpiZpOuihI+k6khlGhkYQDv9Cbk8yVjZ/8O8ZwoyOH351e53H7havdPJ4SXj+1mda2Mms3vcCwPfntv6m59RfLuXr5NoMY9oLe199MWvxx8fXP9B3xs2vZn788imO4Xoa029yPx0fDpZBvoGDZQLlJifUeyQoqqNnrfRsHRRa6cHL9HwdHRlNsmKYsbFkgJGw+D+pGe1094ldpT85BVduSd5Lty1t5VwLU32NjJXpFKEAQIEeqTo+MLqfSMXGWZhTlKsP0d0SO6jlHdo9Do5hy+1VDBCDUn+8+vSo+GFtezs+hxPqEUI+JmcgQ08yrroDhtkNuyqlnZX0d7ukwjoaqyJJGkjSkkQN6RsGt0bhYNT2lWFM0ym0E1Jua/2Mw6uX1yFABkb3u2ir+PTkl4uGzW9oP1R5NFYbPTR2IEvY0rqLl+trBkVnNrfDfRUHOcLdlngrAFTYq1QypUTpD0U/Tu6e3da31aFhECKEfiVMAVOTmKlJAAAeCcrstNgOxTZaYqcfnoV5eXyMkmTFkjHRZEgEiVMTOZ5H9akodcTN76SbNvapoY/VuqxWd51GpgpVaLVyTT1f753UeKn+sk6hdQqucltFqiHF+y31vFPGyrYX71aw8uykrIZdxWqiYzXRDr4+hAsBgF2lP42KH36jy8VdclwO4RTePmsHhEGIEGqWnIHuoaR7KMB/eiciZfPNdFcl/ew8XXRQqnBQYwjEq0k3Nemhg5HRzK1RRNfskEnkPzKGO11zVsmFHL98Kk4T07AuHQCkGVIA4ExN4UVbRYo+6antz/1z/PIP8j+7IzV7TMKIJvemlqnGJY6SqFRhr2IIOV1zNlWfLGOvf3fps+bz6WHdvz67aXL37HO1F8yu2uykLAdfr5ZdOZnv4OvdgjtMafDFm24jvEaIfAOvEQZKYBfdlihUOWmpHcoc9GQt3V1JD5loipaMjiGDwkm8msSoIF5NNNf/hdn5dJk71DsF140utfrvIx/O7TfrZE1BrCY6XGmUqOS96YeXIImUSgXm830iMl478NaTQ/7gvVppcVsFUVDJVMt/em35mMVL8/7xxKB5VfZLF6yld6VOXJD73P+O+3uJtSxCFa6SNXv+vT2uEWIQIt/AIAyUjnb3CV6Cwya65xLNr6Hl9bSyHsocFABSQ8lAIxkcQYZEkH5hXeGEapcJwjbbXbavR1iqzWP77tzWPw955KX9ry8aNn/96Y2R6ojhcUM+PfmFd63z5nhXJG94WM87VTLlJyfWT+o+3lRfc9FWMT5pjLdD+Z/tqUf0MBKx1tVFhIf78I1gECLfwCAMlI4WhE2y8VBopQdN9NBlevAyLayjaaEkXgNxKhKrJvFqSNKSIeGdrOOIQXiN85biFH3ija4q3iSzs9YpuGK10St/fvPpW55Y/cv/jUsazRJ28/kfH+n3oMliio2MvflXaYBBiHwDgzBQOkUQXsMpQIGVXnTARQetqKdlDii00mNm2l1LRkSRYZGkv5GEKUAnJ9oOHI0YhH7jEtwylvOeX8XpEwihrkDJQX8j6W8EuKr3wEtwpIbur6ZbLtKX8yWrByweWi+AXg6xKjLgP6dVBxhJyM3OFEedTCtvPNlmGIQIoQ5BxsDQCDI0gszv/d9GQQIrDxcd9BcTPXiZflIonbLQFC1RcRAqBzVHQliIUkJ/IxkSQXrqcfo/agsMQoRQx8UxYFSAUUEyw8jv0gEA3CIUWKlTABsPdoE6Bahywo4K+nK+VO6gA4ykv5F0U5MoJUSEkFg1xCgJrgCAWoZBiBDqTBQs9Atr6Pf9qgNo9cBhEz1mppX19EQtXHZJFQ646KAyBgaEkwFGMsBI+hiIMYQoWehcA3NQu8IgRAh1ETo5jI0lY2OvPT1a5qBHTPSXGvrJOXrGIpndtF6AegF0ctDISC899AsjfcNIXwPpZcALkMEIgxAh1MXFq0m8mtydeG27xQN1HnqyFvLNdFs5fe24dMZClRxEhJDwEDAqIEJJMnSkTxjprYckLV5+7LIwCBFCQUovB72cJGhgUvyv1hw3uWiNG2pccMlJz1jov05KJ2vB6qG9DEQvh1AZ0clBIwPGo8ysoz31NF2Hq8p1bhiECCH0X2EKCFM0cQ3S4oFTtbSOBxtPLW6wC1BZC1vK6L9OigVWqpFBuo50U5PIEIhSkmgVRISQBA3EqYihfUf+Ix/AIEQIoevTy2FElDcXr6TjpUvOiAiNd0J9uYMW1kG5g152QZWTnrZAtUsqs8NFB/VIkKghsSowhhC9HAwK0MtJmAKStaSHDuI1uPZH4GEQIoTQzYpTkzg1QFOri9l5KHXQcgeY3dTiAYsbaj30fB2sL5IKrFDrpj30JF1HjArQyEAnJ2oO1BxEq0i8GmJVJPzGVsNGbYFBiBBC7Ugjg1560ksPTcakjYcCKz1rpWY3OHiweGhlPTh4uOSUSh1Q4aAOAeLUJCLkyjlb77/GEAhXQKSSRIRAeAgJU4ACB7veBAxChBAKGK0MBoeTweHNnh91CnDRQU1uMLvB7KZmF5jd9IwFLrug2imZXFeG9siZhpiEKBWJDIFIJYlVQUQI0ctBxYFeAWqOKDkIxQmUjWAQIoRQx6XkIE1H0q48ajYv7TyY3dTsBrMbqp202gXVTppXBZddUq0b6gWweq4sxOMUIVwBxhBi/M+/hv/2NUEvJwYF6OSglxOdHGTBsaI4BiFCCHV6GhloZCRB433U0vgbjwQ1Lqhx04Z/vX3NIhuY3WBxSxYPWDxgcVMrD3IGNDLQyoheDloZaGUkVA6hMgiVg0FOtDIIlYNODqEy0vCFRgadblECDEKEEAoicgZiVBCj+tUI2OY4BLDzYOOp1QN1PNg8tI6HOg/U8VDroSV2+M9Dqc4DVg9YPdQugEhBKwOdnBjkEKYAg4IYFGCQg1ZG1DLQcKBXgIYjMgZC5cAS0MlBzoBWRnRyYAIxiBaDECGEUNO8Q1ijlE0v7tocXgI7DxYPNbuh1g21Hmp2g8UNNp7WuMHOe8/TSrwEdR4QKVg84BHBLlCLG0I4UHNXVi3QykArA42M6OSg5kDBgl5OZEBuNxJf3o0QgxAhhJBvyRgwKMCgIMlab8MN9PLqBXAIV1YtsPFgF650Q+08uCWo9VC7m9brfdxtxCBECCHUUag4UHEQEUJA29D2q9jzeESbTfLtiwbHkCCEEEKoGRiECCGEghoGIUIIoaCGQYgQQiioYRAihBAKal0wCO+77z6PxxPoKoLOwYMHly5dGugqgtGqVas2b94c6CqC0ezZs61Wa6CrCDr5+fmLFi3y7T674PSJAwcOSJKPB9ei6zKbzWfOnAl0FcHo/PnzRqNvpxejVjl8+DDP84GuIuhYrdaTJ0/6dp9+CkKbzfbSSy+dPHmyT58+zzzzjFarba69uS0RQgih9uCnU6Pr1q2Liopat25dZGTk+vXrW2hvbkuEEEKoPfipR7hnz55ly5bJ5fIpU6YsXbp07ty5zbU3t+XVJEk6depU47PzKpVKo9EAQGVlZUgI3tfZr8xms9vtrqioCHQhQcfpdFqtVvzk/U+SpKqqKkEQAl1IcDGbzTzPt/6Aj4yM5LjrJJ2fgrCmpiYqKgoAoqKizGZzC+3NbXm1nj173n333Y3blUqlWq1WKBTDhw9vj3eBWiCKoiAIAwYMCHQhQYfn+e3bt69atSrQhQQdSZLGjx9PSCBulxDEJEnieb71v2p+/PHHvn37tryNn4KQUuo9XCilV49kadze3JZX27Jliz+KRgghFAT8dI3QaDRWV1cDgMlkCg8Pb6G9uS0RQgih9uCnIBw2bFhOTg6lNCcnZ8SIEQBw7NixJtsbtyCEEELtx09BOGfOnKKiopkzZxYXF8+aNQsAFi5c2GR74xaEEEKo/RBKaaBrQAghhAKm66wsgzPx/SwvL++jjz4ymUzJyckLFizo1q0bAMyfP//06dPeDSZPnvynP/0poDV2QY0/YTzy/SA7O/ualp49e+Kh3t5EUZw3b94HH3wA7bz6StfpEb733ntOp/Phhx9+++23VSpVkxMQka9UVlY+/PDDL7/8cnJy8jfffLN3795Vq1ZRSqdPn/7ee+8plUoAYFlWLpcHutIupclPGI98P3A6nQ1fr1u3juf5H374AQ/1drVhw4bc3NyCgoJt27ZBU7/hfXjkd51Ft/fs2TNlyhTvTPy8vLxAl9PFVVZWjh07NiMjQ6FQ3H777WVlZQBQU1MjiuLixYtnzJixYsUKh8MR6DK7miY/YTzy/UD5H1VVVadOnZoyZQoe6u0tJSVl9uzZDQ8bH+c+PPK7ThC2ZiY+8pWBAwd6zwWJovjRRx9lZWUBgNlsTktLW7BgwaeffqpWq1evXh3gKrucJj9hPPL9huf5V1999fHHH7dYLHiot7f+/fsPGzas4WHbVl9ppa5zjbA1M/GRbx06dOi9994bPHjw7373OwBIT09fuXKl96l58+bNmzcvoNV1QU1+wnjk+82XX36ZkZGRmJgIAHio+1nbVl9ppa7TI8SZ+P5EKX3nnXc+/fTTJUuWzJs3j2VZADh79mzD7VFkMplMJgtojV1Qk58wHvn+IYri999/P3XqVMBDPRDadfWVrhOEOBPfn/Lz8/ft2/fCCy8YjUan0+kdSuByuZ5//vmSkhKe59esWTNy5MhAl9nVNPkJ45HvH0ePHo2IiIiLiwM81AOhXVdf6TqjRu12+4oVK86fP5+Wlvbss8+q1epAV9SVffzxx5988snVLdu2baOUfvPNNxs2bHA4HEOHDn3iiSfwp+BbTX7CeOT7x4oVK7p16zZnzhxo5gcR6AK7puzsbO+o0cbHuQ+P/K4ThAghhFAbdJ1TowghhFAbYBAihBAKahiECCGEghoGIUIIoaCGQYgQQiioYRAihBAKahiECCGEglrXWWsUoU6n8V3uvLwziH37Qu+//35CQoJvd4tQ14BBiFAgLVq0KNAlIBTsMAgRCqTx48cHugSEgh0GIUIdUWlp6dy5c9euXfv6668fP348IiLivvvuu/pU6s6dO9etW3fx4sX4+PgZM2Z4bwnptWfPns8++6ysrCwpKWn69Onep9xu9xtvvHHo0CGTyZSenj5//vykpCQAqKysfPfdd/Pz891ud3p6+qOPPpqamurnN4tQYOFgGYQ6roULF0ZGRj7xxBMZGRkvv/zyrl27vO27du1avnx53759FyxY0KdPn+XLl+/evdv71P79+1944YUBAwY8/fTTycnJy5cv915x/Otf/0opnT9//mOPPWaxWF555RUAoJQuXrzYZrM98MADjz32mFwuX7p0Kd7UEAUb7BEiFEhNjpdpGCwzevTohx56CADGjRunUqnWrl07ZswYAFizZs3s2bMffPBBAMjKylKpVGvWrBk9ejQAfPzxxw888MCsWbMAYNSoUeXl5Vu3bgWAoUOH/vGPf/TuNi4u7umnnwYAk8lUVlb2yiuvGI1G765Wr15dX1+v0Wja/60j1FFgECIUSO+//34Lz06cOLHh6zvuuOOrr77yeDyU0uLi4mXLljU8lZ2d/emnn3o8HgAoLCx87rnnvO2EkL///e+CIEybNu3qc6cGg8F72xmdTqfX61988cWpU6dmZmZqtdoFCxb49P0h1AlgECIUSC1Pabj6vtuRkZEAYDabvQ+9fbirN2vyKaVS6f3CYDA03r9cLl+5cuUnn3zy0ksvuVyuvn37zps3r1evXm17Lwh1UniNEKGOy2QyXfO1wWDwRlpNTU3DU96vDQaDXq8HAIvF0vBUZWVlfn4+ABBCmnyJxMTEJUuWfP3116tWrdLpdIsXL/b2LBEKHhiECHVcOTk5DV9v2rQpMTFRoVAoFIrExMSrJ91v3bo1KSlJoVCEhIQkJCTk5uY2PPX6669/9NFHze3fYrHMmTPH4XBwHNerV68nn3zSbrfX1dW109tBqGPCU6MIBdKPP/7YZHt6ejoAbNy40eFw9OrV69ixY5s3b168eLH32dmzZ7/44osOh6Nnz56nT5/esGFDw3XBOXPmrFixwuFwpKWlHTly5NChQ0uWLPF2ChvT6XQsyz7//PPZ2dmU0tzc3ISEhKvPrCIUDIj3mjlCyP+aW2INAN5///25c+e+8847b775ZmFhYURExIwZM26//faGDXbs2LFu3bry8vK4uLiZM2d6R5N6bd++ff369eXl5TExMTNmzMjOzr5miTXvJEVvn7K4uPitt94qKCgAgD59+jz66KNxcXHt9YYR6pAwCBHqiK7OKoRQu8JrhAghhIIaBiFCCKGghqdGEeqIXC7XuXPn+vTpE+hCEOr6MAgRQggFNTw1ihBCKKhhECKEEApqGIQIIYSCGgYhQgihoIZBiBBCKKj9fw10NZVfkDvQAAAAAElFTkSuQmCC"
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# overfitting less, loss results improve 0.0841 -> 0.0673\n",
    "plot([mlp2[1,:], mlp2[2,:], mlp4[1,:], mlp4[2,:]], ylim=(0.0,0.15),\n",
    "     labels=[:trnMLP :tstMLP :trnDrop :tstDrop],xlabel=\"Epochs\",ylabel=\"Loss\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# this time error also improves 0.0243 -> 0.0189\n",
    "plot([mlp2[3,:], mlp2[4,:], mlp4[3,:], mlp4[4,:]], ylim=(0.0,0.04),\n",
    "     labels=[:trnMLP :tstMLP :trnDrop :tstDrop],xlabel=\"Epochs\",ylabel=\"Error\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(mlperr = 0.0234f0, L1err = 0.0237f0, dropouterr = 0.0195f0)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(mlperr=minimum(mlp2[4,:]),L1err=minimum(mlp3[4,:]),dropouterr=minimum(mlp4[4,:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(mlploss = 0.07980404f0, L1loss = 0.0801754f0, dropoutloss = 0.06670455f0)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(mlploss=minimum(mlp2[2,:]),L1loss=minimum(mlp3[2,:]),dropoutloss=minimum(mlp4[2,:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## MLP with larger hidden layer and dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train from scratch? stdin> y\n",
      "4.79e-02  100.00%┣████████████████▉┫ 60000/60000 [01:14/01:14, 811.59i/s]\n",
      "Float32[0.00347054; 0.0490601; 0.000233333; 0.0147]\n"
     ]
    }
   ],
   "source": [
    "# The current trend is to use models with higher capacity tempered with dropout\n",
    "# 5.80e-02  100.00%┣████████████████┫ 60000/60000 [00:54/00:54, 1101.25i/s]\n",
    "# [0.0035497; 0.0479644; 0.0003; 0.0149]\n",
    "model = Chain(Layer2(784,256,pdrop=0.2), Layer2(256,10,identity))\n",
    "mlp = trainresults(\"mlp113f.jld2\", model);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Both train and test loss is better with the larger model\n",
    "plot([mlp4[1,:], mlp4[2,:], mlp[1,:], mlp[2,:]],ylim=(0,0.15),\n",
    "    labels=[:trn64 :tst64 :trn256 :tst256],xlabel=\"Epochs\",ylabel=\"Loss\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We are down to 1.5% error.\n",
    "plot([mlp4[3,:], mlp4[4,:], mlp[3,:], mlp[4,:]],ylim=(0,0.04),\n",
    "    labels=[:trn64 :tst64 :trn256 :tst256],xlabel=\"Epochs\",ylabel=\"Error\")"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "julia.ipynb",
   "provenance": [],
   "version": "0.3.2"
  },
  "kernelspec": {
   "display_name": "Julia 1.3.1",
   "language": "julia",
   "name": "julia-1.3"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.3.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
